The Project Snapshot

A 10-minute, scenario-based microlearning module designed to help busy parents understand and confidently manage AI tools in their homes.
Tools: Articulate Storyline 360, Reach360 LMS, Canva (visual design), Google Forms (feedback collection).

The Problem

Problem: Busy parents often lack the confidence or knowledge to evaluate AI tools, particularly as these technologies impact children’s learning and entertainment. Traditional resources are too time-consuming and overly technical.
Goal: To create an engaging, bite-sized e-learning experience that builds AI literacy and critical decision-making skills in under 10 minutes.
Metrics: Pre- and post-assessment feedback, completion rates, and parent-reported confidence gains.

Audience & Context

Audience: Parents aged 20–40 with children aged 6–14.
Context: Delivered asynchronously, accessible across mobile, tablet, and desktop devices. Parents accessed it at home, during work breaks, or while caring for children.
Accessibility Constraints: Mobile-friendly layout, closed captions, clear visual hierarchy, and plain-language content to accommodate varying levels of digital literacy.

My Role & Tools

Role: Instructional Designer, eLearning Developer, Content Creator, and Researcher.

• Conducted learner analysis and needs assessment.
• Designed storyboards, microlearning content, and interaction flow.
• Developed the course in Articulate Storyline 360 and tested deployment in Reach360.
• Collected data through Google Forms and post-session surveys.

Tools:

• Articulate Storyline 360
• Canva (infographics, tip sheets)
• Google Forms (feedback & data collection)
• Reach360 LMS (course hosting and analytics)

Process (Design Model)

The course was developed using a Design-Based Research (DBR) model, emphasizing iterative development, real-world testing, and refinement.

• Analysis: Conducted a needs assessment through informal conversations and parent surveys to identify gaps in AI knowledge.
• Design: Created bite-sized, scenario-based microlearning modules using ADDIE principles (analysis → design → development → implementation → evaluation) embedded within the DBR cycle.
• Prototype: Built an initial version of the module with scenario-based interactions, branching feedback, and quick quizzes.
• Test: Piloted with a small group of parents in both the U.S. and U.K., gathering data on navigation, engagement, and comprehension.
• Iterate: Refined content based on usability findings (e.g., simplifying multiple-choice questions and adding reflection prompts).

The Solution

Live Demo: 
A short, interactive course featuring real-life parenting scenarios involving AI, knowledge checks, and downloadable “AI Parenting Tip Sheets.”

Results / Impact

• 80% of participants reported increased confidence in evaluating AI tools post-module.
• 90% completion rate across all participants.
• Parent feedback: “The content was easy to follow, even while I was multitasking with my baby.”
• Highlighted the effectiveness of mobile-first microlearning for time-constrained adult learners.

What I’d Improve Next

I would add:

• Adaptive assessments that adjust question difficulty based on performance.
• More diverse scenarios, such as managing AI with younger children or different cultural contexts.
• Gamification elements like badges and progress tracking to further motivate engagement.